Mapping Soil-Plant-Water Relationships Using UAV-Based Hyperspectral Imaging

Abstract

Remote sensing technologies offer a non-invasive way to assess soil-plant-water interactions in real-time. This study used UAV-mounted hyperspectral sensors to map canopy temperature, NDVI, and soil moisture variability in a maize-soybean intercropping system. Data were correlated with ground truth from soil probes and plant physiological measurements.
Spatial analysis revealed strong correlations between hyperspectral indices and plant water stress indicators. Precision maps generated from the imagery were used to guide variable-rate irrigation. This study demonstrates the potential of UAV hyperspectral imaging for precision agronomy and sustainable water management.